A collection of personal notes on AI security, focusing on LLM security, penetration testing, red teaming techniques, defensive measures, and secure configurations.
- Red Team Guide - Complete red teaming documentation and resources
- LLM Vulnerabilities - Common vulnerabilities in LLM applications
- Attack Techniques - Methods for testing and bypassing LLM safeguards
- Prompt Injection Automation - Automated testing of prompt injection attacks
- Example Assessment - Step-by-step security assessment walkthrough
- AI Guardrails - Implementation of LLM security controls
(Coming soon)
This repository serves as a knowledge base for:
- Understanding LLM security risks and vulnerabilities
- Exploring red teaming techniques for AI systems
- Implementing defensive measures
- Documenting secure configuration practices
The focus is primarily on practical approaches to AI security, with real-world examples and techniques that can be applied to improve the security posture of AI systems.
Note: These notes are maintained for educational purposes and should be used responsibly and ethically.